code: def get_tokens(g_list):
      tokens = []
      for g in g_list:
          sent_token = []
          dic = g.node_attributes
          for node in dic:
              sent_token.append(node["token"])
              if "ROOT" in sent_token:
                  sent_token.remove("ROOT")
          tokens.append(sent_token)
      return tokens
  
imports: import argparse
  import os
  import torch
  import torch.backends.cudnn
  import torch.multiprocessing
  import torch.optim
  from torch.utils.data import DataLoader
  from graph4nlp.pytorch.data.data import from_batch
  from graph4nlp.pytorch.modules.evaluation.accuracy import Accuracy
  from graph4nlp.pytorch.modules.graph_construction import NodeEmbeddingBasedRefinedGraphConstruction
  from graph4nlp.pytorch.modules.graph_construction.node_embedding_based_graph_construction import NodeEmbeddingBasedGraphConstruction
  from graph4nlp.pytorch.modules.utils.generic_utils import to_cuda
  from conll import ConllDataset
  from conlleval import evaluate
  from dependency_graph_construction_without_tokenize import DependencyBasedGraphConstruction_without_tokenizer
  from line_graph_construction import LineBasedGraphConstruction
  from model import Word2tag
label_desc: Use image node_id 4 for calling a global function with example usage: get_tokens(g_list) and returns: tokens